It has been suggested that the target areas of dopaminergic midbrain neurons, the dorsal (DS) and ventral striatum (VS), are differently involved in reinforcement learning especially as actor and critic. Whereas the critic learns to predict rewards, the actor maintains action values to guide future decisions. The different midbrain connections to the DS and the VS seem to play a critical role in this functional distinction. Here, subjects performed a dynamic, reward-based decision-making task during fMRI acquisition. A computational model of reinforcement learning was used to estimate the different effects of positive and negative reinforcements on future decisions for each subject individually. We found that activity in both the DS and the VS correlated with reward prediction errors. Using functional connectivity, we show that the DS and the VS are differentially connected to different midbrain regions (possibly corresponding to the substantia nigra [SN] and the ventral tegmental area [VTA], respectively). However, only functional connectivity between the DS and the putative SN predicted the impact of different reinforcement types on future behavior. These results suggest that connections between the putative SN and the DS are critical for modulating action values in the DS according to both positive and negative reinforcements to guide future decision making.